We are fresh off an exciting week at Hannover Messe, the world’s leading industrial trade fair, where we had the privilege of showcasing the impact of agentic AI and industrial data operations with Cognite Data Fusion® and Cognite Atlas AI™ at both the Microsoft and Amazon Web Services booths. This year's event came with an array of perspectives on The State of Industrial AI and data management. Here are our takeaways:
1. AI is Everywhere, But Lacking Specificity
AI was the leading topic at Hannover Messe, yet much of the marketing and product demonstrations revealed a market still in its early stages. While the potential of AI is undeniable, many solutions are still immature. This mirrors what we saw at CERAWeek, where discussions centered on separating "hype" from "reality" in AI adoption. At Hannover, like in the energy sector, the focus is shifting to how AI changes daily workflows and delivers tangible value.
Attendees actively sought out practical use cases for Generative AI. The interest is shifting away from the theoretical possibilities and towards the tangible application of GenAI to solve real-world industrial challenges. This reflects a broader trend of moving beyond experimentation to implementation.
We agree with this focus on practical AI applications, which is why our focus is on scaling AI across operations, ensuring it moves beyond PoCs to deliver real OPEX improvements. We do this by providing the robust data foundation necessary for successful AI initiatives, while Cognite Atlas AI accelerates the development and deployment of industrial AI agents tailored to specific, practical applications.
For example, a recent 24-hour Agent Hackathon delivered nine new agents that tackled real-world industrial problems. One example is the AI-Powered Prioritization for Reliability Engineers, which sifts through mountains of data to highlight the most critical work, automates data collection, and streamlines work execution, reducing downtime and boosting production.
2. Knowledge Graphs Gain Traction in the AI Conversation
There was significant interest in knowledge graphs, with attendees keen to understand how they are built, their applications, how to query them, and the scope of underlying data. This highlights a growing recognition of the power of contextualization and data relationships in industrial AI solutions.
Knowledge graphs use machine learning to construct a holistic representation of industrial operations with semantic enrichment. This allows knowledge graphs to discern individual objects and understand the relationships between them by comparing and fusing accumulated knowledge with other relevant datasets. This enables AI-powered queries and search systems to provide comprehensive responses, streamlining manual data collection and integration for better decision-making.
Cognite has long championed the importance of contextualization in building and maintaining a living, real-time industrial knowledge graph. Cognite Data Fusion connects disparate data sources across OT, ET, and IT—structured and unstructured—sources, enabling users to find and use data for deeper insights quickly. This contextualization is crucial for generative AI, as Large Language Models (LLMs) require contextualized data to provide accurate and trustworthy responses. By providing this foundation, Cognite Data Fusion minimizes the risk of "hallucinations" and ensures that AI applications are built on reliable information.
3. Interoperability Beyond APIs
The discussion around data interoperability has evolved beyond the basic idea of point connections through open APIs. Today, for IT professionals in the industrial sector, the core need to deliver business insights requires data to flow freely and meaningfully throughout the enterprise, accelerating solution delivery and delivering an environment for agile innovation with effective governance.
To achieve true interoperability, the meaning, context, and structure of data must be open and accessible for all. Cognite Data Fusion subscribes to this philosophy and offers a composable and secure solution for seamless and meaningful data access to accelerate application development and foster a sustainable technology environment. This approach enables IT to reduce costs, improve ROI, and empower teams to rapidly build, deploy, and scale valuable use cases that extend the value of their existing architecture.
Another key benefit of this approach is scalability. An open platform allows solutions to be connected and validated at a single site and then scaled across multiple sites, ensuring consistency, efficiency, and cost-effectiveness while supporting a rapidly growing and evolving business.
Tangible next steps
Hannover Messe provided invaluable insights into the evolving needs of the industrial sector. It's clear that to thrive, companies must address critical challenges like data interoperability, the strategic application of knowledge graphs, and the effective deployment of practical AI solutions. If these topics are top of mind for you, we can help you navigate the path forward:
- Get Up to Speed on Gen AI for Industry: Discover how to move beyond hype and implement GenAI to transform your operations with our definitive guide.
- Drive tangible results: Explore real-world examples of how organizations are achieving operational excellence by leveraging Cognite's solutions.
- Accelerate your AI journey: Overcome implementation hurdles with our proven approach to rapidly scale impactful AI use cases.